A novel strategy for developing vaccine candidate against Jaagsiekte sheep retrovirus from the envelope and gag proteins: an in-silico approach

Lesion Localization and Pathological Diagnosis of Ovine Pulmonary Adenocarcinoma Based on MASK R-CNN

Ovine pulmonary adenocarcinoma (OPA) is a contagious lung tumour caused by the Jaagsiekte Sheep Retrovirus (JSRV). Histopathological diagnosis is the gold standard for OPA diagnosis. However, interpretation of traditional pathology images is complex and operator dependent. The mask regional convolutional neural network (Mask R-CNN) has emerged as a valuable tool in pathological diagnosis. This study utilized 54 typical OPA whole slide images (WSI) to extract 7167 typical lesion images containing OPA to construct a Common Objects in Context (COCO) dataset for OPA pathological images. The dataset was categorized into training and test sets (8:2 ratio) for model training and validation. Mean average specificity (mASp) and average sensitivity (ASe) were used to evaluate model performance. Six WSI-level pathological images (three OPA and three non-OPA images), not included in the dataset, were used for anti-peeking model validation. A random selection of 500 images, not included in the dataset establishment, was used to compare the performance of the model with assessment by pathologists. Accuracy, sensitivity, specificity, and concordance rate were evaluated. The model achieved a mASp of 0.573 and an ASe of 0.745, demonstrating effective lesion detection and alignment with expert annotation. In Anti-Peeking verification, the model showed good performance in locating OPA lesions and distinguished OPA from non-OPA pathological images. In the random 500-image diagnosis, the model achieved 92.8% accuracy, 100% sensitivity, and 88% specificity. The agreement rates between junior and senior pathologists were 100% and 96.5%, respectively. In conclusion, the Mask R-CNN-based OPA diagnostic model developed for OPA facilitates rapid and accurate diagnosis in practical applications.

Identification of concurrent infection with Jaagsiekte sheep retrovirus and maedi-visna virus in China

IMPORTANCE

Ovine pulmonary adenomatosis (OPA) and maedi-visna disease (MVD) are chronic and progressive infectious diseases in sheep caused by Jaagsiekte sheep retrovirus (JSRV) and maedi-visna virus (MVV), respectively.

OBJECTIVE

To investigate the pathological changes and conduct viral gene analysis of OPA and MVD co-occurrence in Inner Mongolia, China.

METHODS

Using gross pathology, histopathology, immunohistochemistry, ultrastructural pathology, PCR, and sequence analysis, we investigated the concurrent infection of JSRV and MVV in 319 Dorper rams slaughtered in a private slaughterhouse in Inner Mongolia, in 2022.

RESULTS

Of the 319 rams included, 3 showed concurrent JSRV and MVV infection. Gross lung pathology showed diffuse enlargement, consolidation, and greyish-white miliary nodules on the lung surface; the trachea was filled with a white foamy fluid; hilar and mediastinal lymph nodes were significantly enlarged. Histopathology results revealed typical OPA and MVD lesions in the lung tissue. Immunohistochemical results were positive for JSRV envelope protein (Env) in the tumor cells and MVV CA in alveolar macrophages. Transmission electron microscopy showed several virions and autophagosomes in the lung tissue, severely damaged mitochondria, and the induced mitophagy. Nucleotide sequences obtained for JSRV env and MVV gag showed the highest homology with the Inner Mongolian strains of JSRV env (JQ837489) and MVV gag (MW248464).

CONCLUSIONS AND RELEVANCE

Our study confirmed that OPA and MVD co-occurrence and identified the pathological changes in Inner Mongolia, China, thereby providing references for the identification of concurrent JSRV and MVV infections.

Immunoinformatics approach for design novel multi-epitope prophylactic and therapeutic vaccine based on capsid proteins L1 and L2 and oncoproteins E6 and E7 of human papillomavirus 16 and human papillomavirus 18 against cervical cancer

BACKGROUND

This study aimed to identify the optimal protein construction for designing a multi-epitope vaccine with both prophylactic and therapeutic effects against cervical cancer, utilizing an immunoinformatics approach. The construction process involved using capsid epitopes L1 and L2, as well as oncoproteins E5, E6, and E7 from human papillomavirus (HPV) types 16 and 18.

METHODS

An experimental in silico analysis with an immunoinformatics approach was used to develop 2 multi-epitope vaccine constructs (A and B). Further analysis was then conducted to compare the constructs and select the one with the highest potential against cervical cancer.

RESULTS

This study produced 2 antigenic, non-allergenic, and nontoxic multi-epitope vaccine constructs (A and B), which exhibited the ideal physicochemical properties for a vaccine. Further analysis revealed that construct B effectively induced both cellular and humoral immune responses.

CONCLUSION

The multi-epitope vaccine construct B for HPV 16 and 18, designed for both prophylactic and therapeutic purposes, met the development criteria for a cervical cancer vaccine. However, these findings need to be validated through in vitro and in vivo experiments.

Development of a novel multi-epitope vaccine for brucellosis prevention

Brucellosis, a zoonotic disease caused by Brucella, presents a significant threat to both animal and human health. In animals, the disease can lead to infertility, miscarriage, and high fever, while in humans, symptoms may include recurrent fever, fatigue, sweating, hepatosplenomegaly, and joint and muscle pain following infection. Treatment often involves long-term antibiotic therapy, placing a substantial psychological and financial burden on patients. While vaccination is crucial for prevention, current animal vaccines have drawbacks such as residual virulence, and a safe and effective human vaccine is lacking. Hence, the development of a vaccine for brucellosis is imperative. In this study, we utilized bioinformatics methods to design a multi-epitope vaccine targeting Brucella. Targeting Heme transporter BhuA and polysaccharide export protein, we identified antigenic epitopes, including six cytotoxic T lymphocyte (CTL) dominant epitopes, six helper T lymphocyte (HTL) dominant epitopes, one conformation B cell dominant epitope, and three linear B cell dominant epitopes. By linking these epitopes with appropriate linkers and incorporating a Toll-like receptor (TLR) agonist (human beta-defensin-2) and an auxiliary peptide (Pan HLA-DR epitopes), we constructed the multi-epitope vaccine (MEV). The MEV demonstrated high antigenicity, non-toxicity, non-allergenicity, non-human homology, stability, and solubility. Molecular docking analysis and molecular dynamics simulations confirmed the interaction and stability of the MEV with receptors (MHCI, MHCII, TLR4). Codon optimization and in silico cloning validated the translation efficiency and successful expression of MEV in Escherichia coli. Immunological simulations further demonstrated the efficacy of MEV in inducing robust immune responses. In conclusion, our findings suggest that the engineered MEVs have the potential to stimulate both humoral and cellular immune responses, offering valuable insights for the future development of safe and efficient Brucella vaccines.

Immunoinformatics, molecular docking and dynamics simulation approaches unveil a multi epitope-based potent peptide vaccine candidate against avian leukosis virus

Lymphoid leukosis is a poultry neoplastic disease caused by avian leukosis virus (ALV) and is characterized by high morbidity and variable mortality rates in chicks. Currently, no effective treatment and vaccination is the only means to control it. This study exploited the immunoinformatics approaches to construct multi-epitope vaccine against ALV. ABCpred and IEDB servers were used to predict B and T lymphocytes epitopes from the viral proteins, respectively. Antigenicity, allergenicity and toxicity of the epitopes were assessed and used to construct the vaccine with suitable adjuvant and linkers. Secondary and tertiary structures of the vaccine were predicted, refined and validated. Structural errors, solubility, stability, immune simulation, dynamic simulation, docking and in silico cloning were also evaluated.The constructed vaccine was hydrophilic, antigenic and non-allergenic. Ramchandran plot showed most of the residues in the favored and additional allowed regions. ProsA server showed no errors in the vaccine structure. Immune simulation showed significant immunoglobulins and cytokines levels. Stability was enhanced by disulfide engineering and molecular dynamic simulation. Docking of the vaccine with chicken's TLR7 revealed competent binding energies.The vaccine was cloned in pET-30a(+) vector and efficiently expressed in Escherichia coli. This study provided a potent peptide vaccine that could assist in tailoring a rapid and cost-effective vaccine that helps to combat ALV. However, experimental validation is required to assess the vaccine efficiency.

An immunoinformatics analysis: design of a multi-epitope vaccine against Cryptosporidium hominis by employing heat shock protein triggers the innate and adaptive immune responses

Cryptosporidium hominis, an anthropologically transferred species in the Cryptosporidium genus, represents many clinical studies in several countries. Its growth in the recent decade is primarily owing to epidemiologic studies. This parasite has complicated life cycles that require differentiation through a variety of phases of development and passage across two or more hosts throughout their lifetimes. As they move from host to host and environment to environment, pathogenic organisms are continually exposed to unexpected changes in the circumstances under which they develop. Heat shock proteins (HSPs) are targets of the host immune response; they are involved in the progression of diseases and play a significant part in this process. It has been discovered that the immunodominant immunogenic antigens in parasite infections HSPs. In this study, we have generated a multi-epitope vaccine against Cryptosporidium hominis (C. hominis) by using heat shock proteins. The epitopes that were selected had a substantial binding affinity for the B- and T-cell reference set of alleles, a high antigenicity score, a nature that was not allergic, a high solubility, non-toxicity and good binders. The epitopes were incorporated into a chimeric vaccine by using appropriate linkers. In order to increase the immunogenicity of the connected epitopes and effectively activate both innate and adaptive immunity, an adjuvant was attached to the epitopes. We have also analyzed the physiochemical characteristics of the vaccine which were satisfactory and then lead to the development of a 3D model. In addition, the binding confirmation of the vaccine to the TLR-4 innate immune receptor was also determined using molecular docking and molecular dynamics (MD) simulation. The results of this simulation show that the vaccine has a strong binding affinity for TLR4, which indicates that the vaccine is highly effective. In general, the vaccine that has been described here has a good potential for inducing protective and targeted immunogenicity, however, this hypothesis is contingent upon more experimental testing.Communicated by Ramaswamy H. Sarma.

Bionics design of affinity peptide inhibitors for SARS-CoV-2 RBD to block SARS-CoV-2 RBD-ACE2 interactions

Coronavirus Disease 2019 (COVID-19), has already posed serious threats and impacts on the health of the population and the country's economy. Therefore, it is of great theoretical significance and practical application value to better understand the process of COVID-19 infection and develop effective therapeutic drugs. It is known that the receptor-binding structural domain (SARS-CoV-2 RBD) on the spike protein of the novel coronavirus directly mediates its interaction with the host receptor angiotensin-converting enzyme 2 (ACE2), and thus blocking SARS-CoV-2 RBD-ACE2 interaction is capable of inhibiting SARS-CoV-2 infection. Firstly, the interaction mechanism between SARS-CoV-2RBD-ACE2 was explored using molecular dynamics simulation (MD) coupled with molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) free energy calculation method. The results of energy analysis showed that the key residues R403, R408, K417, and Y505 of SARS-CoV-2 RBD and the key residues D30, E37, D38, and Y41 of ACE2 were identified. Therefore, according to the hotspot residues of ACE2 and their distribution, a short peptide library of high-affinity SARS-CoV-2 RBD was constructed. And by using molecular docking virtual screening, six short peptides including DDFEDY, DEFEDY, DEYEDY, DFVEDY, DFHEDY, and DSFEDY with high affinity for SARS-CoV-2 RBD were identified. The results of MD simulation further confirmed that DDFEDY, DEYEDY, and DFVEDY are expected to be effective inhibitors. Finally, the allergenicity, toxicity and solubility properties of the three peptide inhibitors were validated.